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IEEE Trans Biomed Eng. 2017 Sep;64(9):2075-2089. doi: 10.1109/TBME.2016.2631246. Epub 2017 Jan 16.

Unobtrusive and Wearable Systems for Automatic Dietary Monitoring.

Abstract

The threat of obesity, diabetes, anorexia, and bulimia in our society today has motivated extensive research on dietary monitoring. Standard self-report methods such as 24-h recall and food frequency questionnaires are expensive, burdensome, and unreliable to handle the growing health crisis. Long-term activity monitoring in daily living is a promising approach to provide individuals with quantitative feedback that can encourage healthier habits. Although several studies have attempted automating dietary monitoring using wearable, handheld, smart-object, and environmental systems, it remains an open research problem. This paper aims to provide a comprehensive review of wearable and hand-held approaches from 2004 to 2016. Emphasis is placed on sensor types used, signal analysis and machine learning methods, as well as a benchmark of state-of-the art work in this field. Key issues, challenges, and gaps are highlighted to motivate future work toward development of effective, reliable, and robust dietary monitoring systems.

PMID:
28092510
DOI:
10.1109/TBME.2016.2631246
[Indexed for MEDLINE]

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